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Cited by 312Advanced Bandit Algorithms ResearchOptimal Experimental Design MethodsAdvanced Causal Inference Techniques

The DOI matches its Crossref record; 228 of the 235 references it cites were found in a registry or an index.

Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing

Kohavi, Ron, Tang, Diane, Xu, Ya·2020·Cambridge University Press eBooks
DOI 10.1017/9781108653985
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Abstract

Getting numbers is easy; getting numbers you can trust is hard. This practical guide by experimentation leaders at Google, LinkedIn, and Microsoft will teach you how to accelerate innovation using trustworthy online controlled experiments, or A/B tests. Based on practical experiences at companies that each run more than 20,000 controlled experiments a year, the authors share examples, pitfalls, and advice for students and industry professionals getting started with experiments, plus deeper dives into advanced topics for practitioners who want to improve the way they make data-driven decisions. Learn how to • Use the scientific method to evaluate hypotheses using controlled experiments • Define key metrics and ideally an Overall Evaluation Criterion • Test for trustworthiness of the results and alert experimenters to violated assumptions • Build a scalable platform that lowers the marginal cost of experiments close to zero • Avoid pitfalls like carryover effects and Twyman's law • Understand how statistical issues play out in practice.

Overview

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Crossref · 10.1017/9781108653985

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228 of 228 references verified0 citation errors · 0 not checkable

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Citations

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Items 201–228 of 228

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7 of the 235 references couldn’t be matched to a known paper.

Research works printed but not linked: 46

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Metadata

Authors
Kohavi, R., Tang, D., & Xu, Y.
Affiliations
  • Microsoft (United States) (US)
  • Google (United States) (US)
  • LinkedIn (United States) (US)
ORCID
Kohavi, Ron
Venue
Cambridge University Press eBooks
Publisher
Cambridge University Press
Published
2020-03-13
DOI
10.1017/9781108653985
OpenAlex
W3011423189
Cited by
297
References
235
Citations by year
2026: 64 · 2025: 53 · 2024: 46 · 2023: 39 · 2022: 34 · 2021: 19 · 2020: 38
FWCI
16.61
Type
book
Language
en
Open access
closed
Licence
www.cambridge.org/core/terms (unspecified)
Locations
Cambridge University Press eBooks (publishedVersion)
Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Advanced Bandit Algorithms Research
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Keywords
A/B testing, experimentation, data-driven decision making, hypothesis testing, statistical significance, residual effects

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